Siddhisanket Raskar

Data Scientist

Pacific Northwest National Laboratory
sraskar@udel.edu

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Siddhisanket (Sid) Raskar

I am a Data Scientist in the Data Science and Machine Intelligence group at Pacific Northwest National Laboratory. I work on Agentic AI and Large Language Models for scientific applications and scientific machine learning.

I obtained my Ph.D. under the guidance of Guang R. Gao on the topic of "Dataflow Software Pipelining” at the University of Delaware. I also have a Master’s in Computer Science from the University of Delaware and a Bachelor’s in Computer Engineering from the University of Pune, India.

My research interesrts are at the intersection of Machine Learning, High Performance Computing and Computer Architectures.

Research Interests :

• Agentic AI Scientific Computing
• Machine Learning and AI Architectures
• High-Performance Computing
• Computing and Dataflow Models
• Computer Architecture and Systems
• Compilers Technology and Runtime Systems

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Professional Service

• Vice Chair Active member and Vice Chair for IEEE Computer Society Technical Community on Parallel Model and System: DataFlow and Beyond (DFSTC)
• Organizer:
  • Democratizing AI Accelerators for HPC Applications: Challenges, Success, and Support Birds of a Feather Session, SuperComputing 2024. [Website]
  • Programming AI Accelerators for Scientific Computing, Tutorial at Supercomputing 2024, Atlanta, USA. [GitHub]
  • Programming AI Accelerators for Scientific Computing, Tutorial at Supercomputing 2023, Denver, USA. [GitHub]
  • Programming AI Accelerators for Scientific Computing, Tutorial at Supercomputing 2022, Dallas, USA. [GitHub]
• Technical Reviewer EDAS'14, IPDPS’14, ASPLOS'15, DFM’15, CGO'15, ESPM'15 CGO’16, ESPM2’16, ASPLOS’16 ESPM2’18, ICS'18, DFM'19, CCGrid'20, ISC'20, BID'22, MLBench'23, SC'23, HiPC'23, CARLA'23, ICCD'23, Micro'23
• Program Committee BID'22, NPC'22, MLBench'23, HiPC'23, CARLA'23, ICS'24, CARLA'24, ATPESC'24, SC'24
• Session Chair PMAM'23
• Webmaster Postdoctoral Society of Argonne 2021,2022.
• Student Volunteer Supercomputing Conference. 2017,2019,2020.

Selected Talks

• LLM Inference Optimizations [Slides] [GitHub]
  ALCF HPC Hands-on Workshop 2024.
• AI Testbeds Deep Dive and Hands-on [Slides] [GitHub]
  ALCF HPC Hands-on Workshop 2024.
• Intro to AI Series: AI Accelerators [Slides] [Video] [GitHub]
  Introduction to AI-driven Science on Supercomputers 2024.
• Programming Novel AI Accelerators for Scientific Computing [Video]
  The University of Michigan Summer School (SciFM 2024).
• Introduction of AI-testbed and hands-on [Slides]
  Argonne Training Program on Extreme-Scale Computing (ATPESC 2023).
• Introduction on DataFlow Architectures and Trends [Slides]
  Argonne Training Program on Extreme-Scale Computing (ATPESC 2023).
• Introduction of AI-testbed and hands-on” [Slides] [Video]
  Argonne Training Program on Extreme-Scale Computing (ATPESC 2022).
• Overview of AI Testbeds at Argonne [Slides] [Video]
  2022 ALCF Simulation, Data, and Learning Workshop (SDL2022).
• Exploring OpenMP target offloading for the GraphCore architecture [Slides] [Video]
  Lightening talk at LLVM Developer's meeting 2022.
• A pathway to OpenMP In the GraphCore Architecture
  LDRD Expedition Day 2022.
• Overview of AI Testbeds at ANL [Video]
  ALCF Simulation, Data and Learning Workshop (SDL 2021).

Publications